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django/docs/topics/cache.txt

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.. _topics-cache:
========================
Django's cache framework
========================
A fundamental trade-off in dynamic Web sites is, well, they're dynamic. Each
time a user requests a page, the Web server makes all sorts of calculations --
from database queries to template rendering to business logic -- to create the
page that your site's visitor sees. This is a lot more expensive, from a
processing-overhead perspective, than your standard
read-a-file-off-the-filesystem server arrangement.
For most Web applications, this overhead isn't a big deal. Most Web
applications aren't washingtonpost.com or slashdot.org; they're simply small-
to medium-sized sites with so-so traffic. But for medium- to high-traffic
sites, it's essential to cut as much overhead as possible.
That's where caching comes in.
To cache something is to save the result of an expensive calculation so that
you don't have to perform the calculation next time. Here's some pseudocode
explaining how this would work for a dynamically generated Web page::
given a URL, try finding that page in the cache
if the page is in the cache:
return the cached page
else:
generate the page
save the generated page in the cache (for next time)
return the generated page
Django comes with a robust cache system that lets you save dynamic pages so
they don't have to be calculated for each request. For convenience, Django
offers different levels of cache granularity: You can cache the output of
specific views, you can cache only the pieces that are difficult to produce, or
you can cache your entire site.
Django also works well with "upstream" caches, such as Squid
(http://www.squid-cache.org/) and browser-based caches. These are the types of
caches that you don't directly control but to which you can provide hints (via
HTTP headers) about which parts of your site should be cached, and how.
Setting up the cache
====================
The cache system requires a small amount of setup. Namely, you have to tell it
where your cached data should live -- whether in a database, on the filesystem
or directly in memory. This is an important decision that affects your cache's
performance; yes, some cache types are faster than others.
Your cache preference goes in the ``CACHE_BACKEND`` setting in your settings
file. Here's an explanation of all available values for ``CACHE_BACKEND``.
Memcached
---------
By far the fastest, most efficient type of cache available to Django, Memcached
is an entirely memory-based cache framework originally developed to handle high
loads at LiveJournal.com and subsequently open-sourced by Danga Interactive.
It's used by sites such as Facebook and Wikipedia to reduce database access and
dramatically increase site performance.
Memcached is available for free at http://danga.com/memcached/ . It runs as a
daemon and is allotted a specified amount of RAM. All it does is provide a
fast interface for adding, retrieving and deleting arbitrary data in the cache.
All data is stored directly in memory, so there's no overhead of database or
filesystem usage.
After installing Memcached itself, you'll need to install the Memcached Python
bindings, which are not bundled with Django directly. Two versions of this are
available. Choose and install *one* of the following modules:
* The fastest available option is a module called ``cmemcache``, available
at http://gijsbert.org/cmemcache/ .
* If you can't install ``cmemcache``, you can install ``python-memcached``,
available at ftp://ftp.tummy.com/pub/python-memcached/ . If that URL is
no longer valid, just go to the Memcached Web site
(http://www.danga.com/memcached/) and get the Python bindings from the
"Client APIs" section.
.. versionadded:: 1.0
The ``cmemcache`` option is new in 1.0. Previously, only
``python-memcached`` was supported.
To use Memcached with Django, set ``CACHE_BACKEND`` to
``memcached://ip:port/``, where ``ip`` is the IP address of the Memcached
daemon and ``port`` is the port on which Memcached is running.
In this example, Memcached is running on localhost (127.0.0.1) port 11211::
CACHE_BACKEND = 'memcached://127.0.0.1:11211/'
One excellent feature of Memcached is its ability to share cache over multiple
servers. This means you can run Memcached daemons on multiple machines, and the
program will treat the group of machines as a *single* cache, without the need
to duplicate cache values on each machine. To take advantage of this feature,
include all server addresses in ``CACHE_BACKEND``, separated by semicolons.
In this example, the cache is shared over Memcached instances running on IP
address 172.19.26.240 and 172.19.26.242, both on port 11211::
CACHE_BACKEND = 'memcached://172.19.26.240:11211;172.19.26.242:11211/'
In the following example, the cache is shared over Memcached instances running
on the IP addresses 172.19.26.240 (port 11211), 172.19.26.242 (port 11212), and
172.19.26.244 (port 11213)::
CACHE_BACKEND = 'memcached://172.19.26.240:11211;172.19.26.242:11212;172.19.26.244:11213/'
A final point about Memcached is that memory-based caching has one
disadvantage: Because the cached data is stored in memory, the data will be
lost if your server crashes. Clearly, memory isn't intended for permanent data
storage, so don't rely on memory-based caching as your only data storage.
Without a doubt, *none* of the Django caching backends should be used for
permanent storage -- they're all intended to be solutions for caching, not
storage -- but we point this out here because memory-based caching is
particularly temporary.
Database caching
----------------
To use a database table as your cache backend, first create a cache table in
your database by running this command::
python manage.py createcachetable [cache_table_name]
...where ``[cache_table_name]`` is the name of the database table to create.
(This name can be whatever you want, as long as it's a valid table name that's
not already being used in your database.) This command creates a single table
in your database that is in the proper format that Django's database-cache
system expects.
Once you've created that database table, set your ``CACHE_BACKEND`` setting to
``"db://tablename"``, where ``tablename`` is the name of the database table.
In this example, the cache table's name is ``my_cache_table``::
CACHE_BACKEND = 'db://my_cache_table'
The database caching backend uses the same database as specified in your
settings file. You can't use a different database backend for your cache table.
Database caching works best if you've got a fast, well-indexed database server.
Filesystem caching
------------------
To store cached items on a filesystem, use the ``"file://"`` cache type for
``CACHE_BACKEND``. For example, to store cached data in ``/var/tmp/django_cache``,
use this setting::
CACHE_BACKEND = 'file:///var/tmp/django_cache'
Note that there are three forward slashes toward the beginning of that example.
The first two are for ``file://``, and the third is the first character of the
directory path, ``/var/tmp/django_cache``. If you're on Windows, put the
drive letter after the ``file://``, like this::
file://c:/foo/bar
The directory path should be absolute -- that is, it should start at the root
of your filesystem. It doesn't matter whether you put a slash at the end of the
setting.
Make sure the directory pointed-to by this setting exists and is readable and
writable by the system user under which your Web server runs. Continuing the
above example, if your server runs as the user ``apache``, make sure the
directory ``/var/tmp/django_cache`` exists and is readable and writable by the
user ``apache``.
Each cache value will be stored as a separate file whose contents are the
cache data saved in a serialized ("pickled") format, using Python's ``pickle``
module. Each file's name is the cache key, escaped for safe filesystem use.
Local-memory caching
--------------------
If you want the speed advantages of in-memory caching but don't have the
capability of running Memcached, consider the local-memory cache backend. This
cache is multi-process and thread-safe. To use it, set ``CACHE_BACKEND`` to
``"locmem://"``. For example::
CACHE_BACKEND = 'locmem://'
Note that each process will have its own private cache instance, which means no
cross-process caching is possible. This obviously also means the local memory
cache isn't particularly memory-efficient, so it's probably not a good choice
for production environments. It's nice for development.
Dummy caching (for development)
-------------------------------
Finally, Django comes with a "dummy" cache that doesn't actually cache -- it
just implements the cache interface without doing anything.
This is useful if you have a production site that uses heavy-duty caching in
various places but a development/test environment where you don't want to cache
and don't want to have to change your code to special-case the latter. To
activate dummy caching, set ``CACHE_BACKEND`` like so::
CACHE_BACKEND = 'dummy://'
Using a custom cache backend
----------------------------
.. versionadded:: 1.0
While Django includes support for a number of cache backends out-of-the-box,
sometimes you might want to use a customized cache backend. To use an external
cache backend with Django, use a Python import path as the scheme portion (the
part before the initial colon) of the ``CACHE_BACKEND`` URI, like so::
CACHE_BACKEND = 'path.to.backend://'
If you're building your own backend, you can use the standard cache backends
as reference implementations. You'll find the code in the
``django/core/cache/backends/`` directory of the Django source.
Note: Without a really compelling reason, such as a host that doesn't support
them, you should stick to the cache backends included with Django. They've
been well-tested and are easy to use.
CACHE_BACKEND arguments
-----------------------
Each cache backend may take arguments. They're given in query-string style on
the ``CACHE_BACKEND`` setting. Valid arguments are as follows:
* ``timeout``: The default timeout, in seconds, to use for the cache.
This argument defaults to 300 seconds (5 minutes).
* ``max_entries``: For the ``locmem``, ``filesystem`` and ``database``
backends, the maximum number of entries allowed in the cache before old
values are deleted. This argument defaults to 300.
* ``cull_frequency``: The fraction of entries that are culled when
``max_entries`` is reached. The actual ratio is ``1/cull_frequency``, so
set ``cull_frequency=2`` to cull half of the entries when ``max_entries``
is reached.
A value of ``0`` for ``cull_frequency`` means that the entire cache will
be dumped when ``max_entries`` is reached. This makes culling *much*
faster at the expense of more cache misses.
In this example, ``timeout`` is set to ``60``::
CACHE_BACKEND = "memcached://127.0.0.1:11211/?timeout=60"
In this example, ``timeout`` is ``30`` and ``max_entries`` is ``400``::
CACHE_BACKEND = "locmem://?timeout=30&max_entries=400"
Invalid arguments are silently ignored, as are invalid values of known
arguments.
The per-site cache
==================
.. versionchanged:: 1.0
(previous versions of Django only provided a single ``CacheMiddleware`` instead
of the two pieces described below).
Once the cache is set up, the simplest way to use caching is to cache your
entire site. You'll need to add
``'django.middleware.cache.UpdateCacheMiddleware'`` and
``'django.middleware.cache.FetchFromCacheMiddleware'`` to your
``MIDDLEWARE_CLASSES`` setting, as in this example::
MIDDLEWARE_CLASSES = (
'django.middleware.cache.UpdateCacheMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.cache.FetchFromCacheMiddleware',
)
.. note::
No, that's not a typo: the "update" middleware must be first in the list,
and the "fetch" middleware must be last. The details are a bit obscure, but
see `Order of MIDDLEWARE_CLASSES`_ below if you'd like the full story.
Then, add the following required settings to your Django settings file:
* ``CACHE_MIDDLEWARE_SECONDS`` -- The number of seconds each page should be
cached.
* ``CACHE_MIDDLEWARE_KEY_PREFIX`` -- If the cache is shared across multiple
sites using the same Django installation, set this to the name of the site,
or some other string that is unique to this Django instance, to prevent key
collisions. Use an empty string if you don't care.
The cache middleware caches every page that doesn't have GET or POST
parameters. Optionally, if the ``CACHE_MIDDLEWARE_ANONYMOUS_ONLY`` setting is
``True``, only anonymous requests (i.e., not those made by a logged-in user)
will be cached. This is a simple and effective way of disabling caching for any
user-specific pages (include Django's admin interface). Note that if you use
``CACHE_MIDDLEWARE_ANONYMOUS_ONLY``, you should make sure you've activated
``AuthenticationMiddleware``.
Additionally, the cache middleware automatically sets a few headers in each
``HttpResponse``:
* Sets the ``Last-Modified`` header to the current date/time when a fresh
(uncached) version of the page is requested.
* Sets the ``Expires`` header to the current date/time plus the defined
``CACHE_MIDDLEWARE_SECONDS``.
* Sets the ``Cache-Control`` header to give a max age for the page --
again, from the ``CACHE_MIDDLEWARE_SECONDS`` setting.
See :ref:`topics-http-middleware` for more on middleware.
.. versionadded:: 1.0
If a view sets its own cache expiry time (i.e. it has a ``max-age`` section in
its ``Cache-Control`` header) then the page will be cached until the expiry
time, rather than ``CACHE_MIDDLEWARE_SECONDS``. Using the decorators in
``django.views.decorators.cache`` you can easily set a view's expiry time
(using the ``cache_control`` decorator) or disable caching for a view (using
the ``never_cache`` decorator). See the `using other headers`__ section for
more on these decorators.
__ `Controlling cache: Using other headers`_
The per-view cache
==================
A more granular way to use the caching framework is by caching the output of
individual views. ``django.views.decorators.cache`` defines a ``cache_page``
decorator that will automatically cache the view's response for you. It's easy
to use::
from django.views.decorators.cache import cache_page
def my_view(request):
...
my_view = cache_page(my_view, 60 * 15)
Or, using Python 2.4's decorator syntax::
@cache_page(60 * 15)
def my_view(request):
...
``cache_page`` takes a single argument: the cache timeout, in seconds. In the
above example, the result of the ``my_view()`` view will be cached for 15
minutes. (Note that we've written it as ``60 * 15`` for the purpose of
readability. ``60 * 15`` will be evaluated to ``900`` -- that is, 15 minutes
multiplied by 60 seconds per minute.)
The per-view cache, like the per-site cache, is keyed off of the URL. If
multiple URLs point at the same view, each URL will be cached separately.
Continuing the ``my_view`` example, if your URLconf looks like this::
urlpatterns = ('',
(r'^foo/(\d{1,2})/$', my_view),
)
then requests to ``/foo/1/`` and ``/foo/23/`` will be cached separately, as
you may expect. But once a particular URL (e.g., ``/foo/23/``) has been
requested, subsequent requests to that URL will use the cache.
``cache_page`` can also take an optional keyword argument, ``key_prefix``, which
works in the same way as the ``CACHE_MIDDLEWARE_KEY_PREFIX`` setting for the
middleware. It can be used like this::
my_view = cache_page(my_view, 60 * 15, key_prefix="site1")
Or, using Python 2.4's decorator syntax::
@cache_page(60 * 15, key_prefix="site1")
def my_view(request):
Specifying per-view cache in the URLconf
----------------------------------------
The examples in the previous section have hard-coded the fact that the view is
cached, because ``cache_page`` alters the ``my_view`` function in place. This
approach couples your view to the cache system, which is not ideal for several
reasons. For instance, you might want to reuse the view functions on another,
cache-less site, or you might want to distribute the views to people who might
want to use them without being cached. The solution to these problems is to
specify the per-view cache in the URLconf rather than next to the view functions
themselves.
Doing so is easy: simply wrap the view function with ``cache_page`` when you
refer to it in the URLconf. Here's the old URLconf from earlier::
urlpatterns = ('',
(r'^foo/(\d{1,2})/$', my_view),
)
Here's the same thing, with ``my_view`` wrapped in ``cache_page``::
from django.views.decorators.cache import cache_page
urlpatterns = ('',
(r'^foo/(\d{1,2})/$', cache_page(my_view, 60 * 15)),
)
If you take this approach, don't forget to import ``cache_page`` within your
URLconf.
Template fragment caching
=========================
.. versionadded:: 1.0
If you're after even more control, you can also cache template fragments using
the ``cache`` template tag. To give your template access to this tag, put
``{% load cache %}`` near the top of your template.
The ``{% cache %}`` template tag caches the contents of the block for a given
amount of time. It takes at least two arguments: the cache timeout, in seconds,
and the name to give the cache fragment. For example::
{% load cache %}
{% cache 500 sidebar %}
.. sidebar ..
{% endcache %}
Sometimes you might want to cache multiple copies of a fragment depending on
some dynamic data that appears inside the fragment. For example, you might want a
separate cached copy of the sidebar used in the previous example for every user
of your site. Do this by passing additional arguments to the ``{% cache %}``
template tag to uniquely identify the cache fragment::
{% load cache %}
{% cache 500 sidebar request.user.username %}
.. sidebar for logged in user ..
{% endcache %}
It's perfectly fine to specify more than one argument to identify the fragment.
Simply pass as many arguments to ``{% cache %}`` as you need.
The cache timeout can be a template variable, as long as the template variable
resolves to an integer value. For example, if the template variable
``my_timeout`` is set to the value ``600``, then the following two examples are
equivalent::
{% cache 600 sidebar %} ... {% endcache %}
{% cache my_timeout sidebar %} ... {% endcache %}
This feature is useful in avoiding repetition in templates. You can set the
timeout in a variable, in one place, and just reuse that value.
The low-level cache API
=======================
Sometimes, caching an entire rendered page doesn't gain you very much and is,
in fact, inconvenient overkill.
Perhaps, for instance, your site includes a view whose results depend on
several expensive queries, the results of which change at different intervals.
In this case, it would not be ideal to use the full-page caching that the
per-site or per-view cache strategies offer, because you wouldn't want to
cache the entire result (since some of the data changes often), but you'd still
want to cache the results that rarely change.
For cases like this, Django exposes a simple, low-level cache API. You can use
this API to store objects in the cache with any level of granularity you like.
You can cache any Python object that can be pickled safely: strings,
dictionaries, lists of model objects, and so forth. (Most common Python objects
can be pickled; refer to the Python documentation for more information about
pickling.)
The cache module, ``django.core.cache``, has a ``cache`` object that's
automatically created from the ``CACHE_BACKEND`` setting::
>>> from django.core.cache import cache
The basic interface is ``set(key, value, timeout)`` and ``get(key)``::
>>> cache.set('my_key', 'hello, world!', 30)
>>> cache.get('my_key')
'hello, world!'
The ``timeout`` argument is optional and defaults to the ``timeout``
argument in the ``CACHE_BACKEND`` setting (explained above). It's the number of
seconds the value should be stored in the cache.
If the object doesn't exist in the cache, ``cache.get()`` returns ``None``::
# Wait 30 seconds for 'my_key' to expire...
>>> cache.get('my_key')
None
We advise against storing the literal value ``None`` in the cache, because you
won't be able to distinguish between your stored ``None`` value and a cache
miss signified by a return value of ``None``.
``cache.get()`` can take a ``default`` argument. This specifies which value to
return if the object doesn't exist in the cache::
>>> cache.get('my_key', 'has expired')
'has expired'
.. versionadded:: 1.0
To add a key only if it doesn't already exist, use the ``add()`` method.
It takes the same parameters as ``set()``, but it will not attempt to
update the cache if the key specified is already present::
>>> cache.set('add_key', 'Initial value')
>>> cache.add('add_key', 'New value')
>>> cache.get('add_key')
'Initial value'
If you need to know whether ``add()`` stored a value in the cache, you can
check the return value. It will return ``True`` if the value was stored,
``False`` otherwise.
There's also a ``get_many()`` interface that only hits the cache once.
``get_many()`` returns a dictionary with all the keys you asked for that
actually exist in the cache (and haven't expired)::
>>> cache.set('a', 1)
>>> cache.set('b', 2)
>>> cache.set('c', 3)
>>> cache.get_many(['a', 'b', 'c'])
{'a': 1, 'b': 2, 'c': 3}
.. versionadded:: 1.2
To set multiple values more efficiently, use ``set_many()`` to pass a dictionary
of key-value pairs::
>>> cache.set_many({'a': 1, 'b': 2, 'c': 3})
>>> cache.get_many(['a', 'b', 'c'])
{'a': 1, 'b': 2, 'c': 3}
Like ``cache.set()``, ``set_many()`` takes an optional ``timeout`` parameter.
You can delete keys explicitly with ``delete()``. This is an easy way of
clearing the cache for a particular object::
>>> cache.delete('a')
.. versionadded:: 1.2
If you want to clear a bunch of keys at once, ``delete_many()`` can take a list
of keys to be cleared::
>>> cache.delete_many(['a', 'b', 'c'])
.. versionadded:: 1.2
Finally, if you want to delete all the keys in the cache, use
``cache.clear()``. Be careful with this; ``clear()`` will remove *everything*
from the cache, not just the keys set by your application. ::
>>> cache.clear()
.. versionadded:: 1.1
You can also increment or decrement a key that already exists using the
``incr()`` or ``decr()`` methods, respectively. By default, the existing cache
value will incremented or decremented by 1. Other increment/decrement values
can be specified by providing an argument to the increment/decrement call. A
ValueError will be raised if you attempt to increment or decrement a
nonexistent cache key.::
>>> cache.set('num', 1)
>>> cache.incr('num')
2
>>> cache.incr('num', 10)
12
>>> cache.decr('num')
11
>>> cache.decr('num', 5)
6
.. note::
``incr()``/``decr()`` methods are not guaranteed to be atomic. On those
backends that support atomic increment/decrement (most notably, the
memcached backend), increment and decrement operations will be atomic.
However, if the backend doesn't natively provide an increment/decrement
operation, it will be implemented using a two-step retrieve/update.
Upstream caches
===============
So far, this document has focused on caching your *own* data. But another type
of caching is relevant to Web development, too: caching performed by "upstream"
caches. These are systems that cache pages for users even before the request
reaches your Web site.
Here are a few examples of upstream caches:
* Your ISP may cache certain pages, so if you requested a page from
http://example.com/, your ISP would send you the page without having to
access example.com directly. The maintainers of example.com have no
knowledge of this caching; the ISP sits between example.com and your Web
browser, handling all of the caching transparently.
* Your Django Web site may sit behind a *proxy cache*, such as Squid Web
Proxy Cache (http://www.squid-cache.org/), that caches pages for
performance. In this case, each request first would be handled by the
proxy, and it would be passed to your application only if needed.
* Your Web browser caches pages, too. If a Web page sends out the
appropriate headers, your browser will use the local cached copy for
subsequent requests to that page, without even contacting the Web page
again to see whether it has changed.
Upstream caching is a nice efficiency boost, but there's a danger to it:
Many Web pages' contents differ based on authentication and a host of other
variables, and cache systems that blindly save pages based purely on URLs could
expose incorrect or sensitive data to subsequent visitors to those pages.
For example, say you operate a Web e-mail system, and the contents of the
"inbox" page obviously depend on which user is logged in. If an ISP blindly
cached your site, then the first user who logged in through that ISP would have
his user-specific inbox page cached for subsequent visitors to the site. That's
not cool.
Fortunately, HTTP provides a solution to this problem. A number of HTTP headers
exist to instruct upstream caches to differ their cache contents depending on
designated variables, and to tell caching mechanisms not to cache particular
pages. We'll look at some of these headers in the sections that follow.
Using Vary headers
==================
The ``Vary`` header defines which request headers a cache
mechanism should take into account when building its cache key. For example, if
the contents of a Web page depend on a user's language preference, the page is
said to "vary on language."
By default, Django's cache system creates its cache keys using the requested
path (e.g., ``"/stories/2005/jun/23/bank_robbed/"``). This means every request
to that URL will use the same cached version, regardless of user-agent
differences such as cookies or language preferences. However, if this page
produces different content based on some difference in request headers -- such
as a cookie, or a language, or a user-agent -- you'll need to use the ``Vary``
header to tell caching mechanisms that the page output depends on those things.
To do this in Django, use the convenient ``vary_on_headers`` view decorator,
like so::
from django.views.decorators.vary import vary_on_headers
@vary_on_headers('User-Agent')
def my_view(request):
# ...
In this case, a caching mechanism (such as Django's own cache middleware) will
cache a separate version of the page for each unique user-agent.
The advantage to using the ``vary_on_headers`` decorator rather than manually
setting the ``Vary`` header (using something like
``response['Vary'] = 'user-agent'``) is that the decorator *adds* to the
``Vary`` header (which may already exist), rather than setting it from scratch
and potentially overriding anything that was already in there.
You can pass multiple headers to ``vary_on_headers()``::
@vary_on_headers('User-Agent', 'Cookie')
def my_view(request):
# ...
This tells upstream caches to vary on *both*, which means each combination of
user-agent and cookie will get its own cache value. For example, a request with
the user-agent ``Mozilla`` and the cookie value ``foo=bar`` will be considered
different from a request with the user-agent ``Mozilla`` and the cookie value
``foo=ham``.
Because varying on cookie is so common, there's a ``vary_on_cookie``
decorator. These two views are equivalent::
@vary_on_cookie
def my_view(request):
# ...
@vary_on_headers('Cookie')
def my_view(request):
# ...
The headers you pass to ``vary_on_headers`` are not case sensitive;
``"User-Agent"`` is the same thing as ``"user-agent"``.
You can also use a helper function, ``django.utils.cache.patch_vary_headers``,
directly. This function sets, or adds to, the ``Vary header``. For example::
from django.utils.cache import patch_vary_headers
def my_view(request):
# ...
response = render_to_response('template_name', context)
patch_vary_headers(response, ['Cookie'])
return response
``patch_vary_headers`` takes an ``HttpResponse`` instance as its first argument
and a list/tuple of case-insensitive header names as its second argument.
For more on Vary headers, see the `official Vary spec`_.
.. _`official Vary spec`: http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html#sec14.44
Controlling cache: Using other headers
======================================
Other problems with caching are the privacy of data and the question of where
data should be stored in a cascade of caches.
A user usually faces two kinds of caches: his or her own browser cache (a
private cache) and his or her provider's cache (a public cache). A public cache
is used by multiple users and controlled by someone else. This poses problems
with sensitive data--you don't want, say, your bank account number stored in a
public cache. So Web applications need a way to tell caches which data is
private and which is public.
The solution is to indicate a page's cache should be "private." To do this in
Django, use the ``cache_control`` view decorator. Example::
from django.views.decorators.cache import cache_control
@cache_control(private=True)
def my_view(request):
# ...
This decorator takes care of sending out the appropriate HTTP header behind the
scenes.
There are a few other ways to control cache parameters. For example, HTTP
allows applications to do the following:
* Define the maximum time a page should be cached.
* Specify whether a cache should always check for newer versions, only
delivering the cached content when there are no changes. (Some caches
might deliver cached content even if the server page changed, simply
because the cache copy isn't yet expired.)
In Django, use the ``cache_control`` view decorator to specify these cache
parameters. In this example, ``cache_control`` tells caches to revalidate the
cache on every access and to store cached versions for, at most, 3,600 seconds::
from django.views.decorators.cache import cache_control
@cache_control(must_revalidate=True, max_age=3600)
def my_view(request):
# ...
Any valid ``Cache-Control`` HTTP directive is valid in ``cache_control()``.
Here's a full list:
* ``public=True``
* ``private=True``
* ``no_cache=True``
* ``no_transform=True``
* ``must_revalidate=True``
* ``proxy_revalidate=True``
* ``max_age=num_seconds``
* ``s_maxage=num_seconds``
For explanation of Cache-Control HTTP directives, see the `Cache-Control spec`_.
(Note that the caching middleware already sets the cache header's max-age with
the value of the ``CACHE_MIDDLEWARE_SETTINGS`` setting. If you use a custom
``max_age`` in a ``cache_control`` decorator, the decorator will take
precedence, and the header values will be merged correctly.)
If you want to use headers to disable caching altogether,
``django.views.decorators.cache.never_cache`` is a view decorator that adds
headers to ensure the response won't be cached by browsers or other caches.
Example::
from django.views.decorators.cache import never_cache
@never_cache
def myview(request):
# ...
.. _`Cache-Control spec`: http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html#sec14.9
Other optimizations
===================
Django comes with a few other pieces of middleware that can help optimize your
site's performance:
* ``django.middleware.http.ConditionalGetMiddleware`` adds support for
modern browsers to conditionally GET responses based on the ``ETag``
and ``Last-Modified`` headers.
* ``django.middleware.gzip.GZipMiddleware`` compresses responses for all
moderns browsers, saving bandwidth and transfer time.
Order of MIDDLEWARE_CLASSES
===========================
If you use caching middleware, it's important to put each half in the right
place within the ``MIDDLEWARE_CLASSES`` setting. That's because the cache
middleware needs to know which headers by which to vary the cache storage.
Middleware always adds something to the ``Vary`` response header when it can.
``UpdateCacheMiddleware`` runs during the response phase, where middleware is
run in reverse order, so an item at the top of the list runs *last* during the
response phase. Thus, you need to make sure that ``UpdateCacheMiddleware``
appears *before* any other middleware that might add something to the ``Vary``
header. The following middleware modules do so:
* ``SessionMiddleware`` adds ``Cookie``
* ``GZipMiddleware`` adds ``Accept-Encoding``
* ``LocaleMiddleware`` adds ``Accept-Language``
``FetchFromCacheMiddleware``, on the other hand, runs during the request phase,
where middleware is applied first-to-last, so an item at the top of the list
runs *first* during the request phase. The ``FetchFromCacheMiddleware`` also
needs to run after other middleware updates the ``Vary`` header, so
``FetchFromCacheMiddleware`` must be *after* any item that does so.